Cell-Mediated Immunity to Predict Cytomegalovirus Disease in High-Risk Solid Organ Transplant Recipients
Bibliographic record
Abstract
Late-onset cytomegalovirus (CMV) disease commonly occurs after discontinuation of antiviral prophylaxis. We determined the utility of testing CD8+ T-cell response against CMV as a predictor of late-onset CMV disease after a standard course of antiviral prophylaxis. Transplant patients at high-risk for CMV disease were enrolled. CD8+ T-cell-mediated immunity (CMI) was tested using the QuantiFERON-CMV assay at baseline, 1, 2 and 3 months posttransplant by measurement of interferon-gamma response to whole blood stimulation with a 21-peptide pool. The primary outcome was the ability of CMI testing to predict CMV disease in the first 6 months posttransplant. There were 108 evaluable patients (D+/R+ n = 39; D-/R+ n = 34; D+/R- n = 35) of whom 18 (16.7%) developed symptomatic CMV disease. At the end of prophylaxis, CMI was detectable in 38/108 (35.2%) patients (cutoff 0.1 IU/mL interferon-gamma). CMV disease occurred in 2/38 (5.3%) patients with a detectable interferon-gamma response versus 16/70 (22.9%) patients with a negative response; p = 0.038. In the subgroup of D+/R- patients, CMV disease occurred in 1/10 (10.0%) patients with a detectable interferon-gamma response (cutoff 0.1 IU/mL) versus 10/25 (40.0%) patients with a negative CMI, p = 0.12. Monitoring of CMI may be useful for predicting late-onset CMV disease.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".